Researchers Teach Robots Deception by Mimicking Squirrels

Squirrels aren't exactly the first thing that come to mind when you think of withholding the truth, but researchers have used the bushy-tailed creatures to teach robots to do exactly that.

Researchers at the Georgia Institute of Technology at the behest of the Office of Naval Research have developed technology that can allow robots to deceive each other, much in the same way squirrels do when trying to protect their hidden acorns. The military could one day use the robots to protect ammunition or supply stores in combat situations or on the battlefield.

"We have developed algorithms that allow a robot to determine whether it should deceive a human or other intelligent machine and we have designed techniques that help the robot select the best deceptive strategy to reduce its chance of being discovered," said Ronald Arkin, a Regents professor in the Georgia Tech School of Interactive Computing, in a press release.

Georgia Tech researchers Ronald Arkin and Alan Wagner pose with robots that have been trained to deceive each other by studying the behavior of squirrels trying to protect their food stash. The work funded by the Office of Naval Research could eventually be used by the US military. (Source: Georgia Tech)

Researchers used the behavior of squirrels when storing food to develop the algorithms. Squirrels store their acorns in specific locations and routinely keep an eye on those spots to ensure the food is still there. When other squirrels are near a food store, the possessive squirrel will try to lure them away by visiting spots where no acorns are stored and treating those spots in a similar manner. In nature, this behavior works.

Researchers also used a type of bird found in the Middle East called the Arabian babbler to develop the algorithms. These birds distract a predator bird by joining with other birds and attacking a predator in a fake show of force. The deception technique can inspire the predator to give up the hunt.

To prove that the deception technology works in robots, Georgia Tech researchers dispatched two autonomous robots to play 20 games of hide-and-seek. Researchers lined up colored markers along three potential pathways to places where one of the robots could hide, while the other robot sought to find it. On the way to the spot, the hiding robot would knock down the colored markers. To deceive the seeking robot, the hiding robot would proceed to a hiding spot and knock down the markers, but then change course and hide in another location that couldn't be discerned from the displaced markers. The seeking robot used the presence or absence of markers to find the hiding spot.

The hiding robot was successful at deceiving the other robot in 75 percent of tests, researchers said. Failures occurred when the hiding robot did not knock over the appropriate markers to accurately deceive the seeking robot. "The experimental results weren't perfect, but they demonstrated the learning and use of deception signals by real robots in a noisy environment," said Georgia Tech Institute research engineer Alan Wagner in the press release.

Robotics researchers already have been using the movements of animals, birds, and insects in their design of robot movements for some time, but now animal behavior is becoming increasingly more relevant for the design of robot intelligence. In other work, researchers in the UK are working on computer models of a honey bee's brain to create a robot that can think like the flying insect.

In my coverage of robots, it always interests me how researchers try to mimic the natural world to create robots not just for movements, but also for artificial intelligence. Squirrels are a clever choice for this type of deceptive behavior.

Thanks for this fun article, Elizabeth! Biomimetics has long been an intriguing area of research. Quorum Sensing in bacteria is one of the latest discoveries that may well revolutionize how we deal with infectious disease. The folks at Georgia Tech are doing great work. A major difficulty arises when the robots playing hide and seek are not limited by the relatively few senses used by a squirrel. Add multispectral vision, penetrating radar, and residual trace chemical detection and it will be very difficult to hide from the seeker. And then you add a swarm of tiny seekers that just flood the area and check out every hiding place in parallel, and the game is no longer fun. =]

Interesting article, Liz. It's amazing to see the strategies that are being used to teach machines to learn and think. A couple of years ago, we ran a story about robots using humor to make themselves more acceptable to humans. To do that, the robots had to understand humor and have a vague understanding of what's "appropriate," which, of course, is a big part of humor. I can't imagine what robots will be capable of in 50 years.

Thanks, Charles. Humor in robots! Now that would be something. Sometimes you can't even find that in human beings. :) Joking aside, I am with you. I hope I am still around in about 50 years to see how robots have evolved. But I bet it won't even take that long before they are sophisticated beyond most people's imaginations.

Why chase squirrels when you can simply pick up a book on WWII military intelligence? For example, before D-Day, the RAF was tasked with knocking out the German radars on the landing sites. So as not to give away the sites, the RAF targeted 3 other sites for every sortie on the designated beaches. These robots are basically carrying out a similar tactic. What the robots can't do is change tactics once they know that the other side is "on" to them - their behaviour, although irrational, is predictable.

Researchers said the hiding robot "was successful at deceiving the other robot in 75 percent of tests" but can they deceive a second time? Or do we end up with dueling algorithms where the second robot is learning from its mistake .. and they battle to a standoff?

It's amazing how much effort in the area of artificial intelligence is trying to create what the world already does. The difficulty with this is the fact that we occasionally do something that is not predictable and how can an algorythm ever predict something that just comes out of no where.

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